AI and IoT serve as critical cornerstones of smart manufacturing, bringing about digital transformation in the industrial sector.
Welcome to the first episode of ” Jom ! lets Sembang AIoT,” our live channel dedicated to discussing Industrial IoT and AI for smart manufacturing.
Before we delve deeper into our subject, let’s remind ourselves of the four foundational design principles of Industry 4.0, which guide the evolution and implementation of the Fourth Industrial Revolution:
Interoperability: This principle emphasizes the need for machines, devices, sensors, and people to connect and communicate with each other. Interoperability allows for the seamless sharing of information across different systems and stakeholders. This can involve the Internet of Things (IoT), Internet of People (IoP), and other connected technologies.
Information Transparency: With Industry 4.0, the collection and communication of information become much more seamless and transparent, providing operators with vast amounts of useful data. By utilizing digital context to physical processes, a virtual copy of the physical world can be created. This is often referred to as a “Digital Twin”. These digital models can then be used to analyze data and predict trends, helping decision-makers understand and anticipate issues before they arise.
Technical Assistance: This principle concerns the ability of assistance systems to support humans by aggregating and visualizing information comprehensibly for making informed decisions and solving urgent problems on short notice. Moreover, it includes the capability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for humans.
Decentralized Decisions: Industry 4.0 systems are capable of making decisions on their own and performing their tasks as autonomously as possible. This principle refers to the ability of cyber-physical systems to take decisions on their own and to perform their tasks as autonomously as possible. If a conflict arises, a decentralized decision is required to be made in real-time.
The combination of Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) forms the backbone of the fourth industrial revolution, as these technologies inherently support the processes integral to Industry 4.0.
IIoT enhances connectivity from the most fundamental sensors and input-output systems to controllers, equipment, and SCADA systems, reaching all the way to cloud platforms. This interconnectivity ensures decentralization and transparency, enabling swifter, informed decision-making. Additionally, AI and machine learning, driven by the rich data environment of IIoT, allow for precision in decision-making.
In today’s interactive session, we are excited to introduce the application of an industrial computer system and a vision camera to perform deep learning and inferencing on the sample production of a 3-pin AC plug. The computer system employed is the Axiomtek ebox 640-521, an 8th/9th gen Intel-based fanless system with built-in IO, which can seamlessly interface with existing controllers for automation tasks.
The proof-of-concept for Vision AI is composed of four steps:
Gathering a dataset with the cameras
Labelling the collected datasets
Utilizing deep learning AI processes to create a model
Running inference to yield desired results
This approach leads to two substantial benefits:
Minimization of human intervention, thereby conserving manpower
Boosting efficiency and accuracy
However, our exploration doesn’t stop there. We can collect essential data such as the number and types of defects, which can be uploaded to the cloud or big data for further analysis. Such analytics, powered by AI, can enhance forecasting and optimize the overall process.
Watch the video here